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What is Sigma AI?
Sigma AI specializes in providing high-quality annotated data essential for training sophisticated AI models, particularly Large Language Models (LLMs) and Generative AI. With capabilities spanning over 500 languages and dialects, they leverage a global team of expert annotators, translators, and linguists to achieve up to 99.99% accuracy, even for complex and ambiguous tasks. Their services are designed to handle demanding projects at any scale, ensuring the reliability and effectiveness of AI applications.
Drawing on extensive experience in the data annotation field, Sigma AI assists clients in overcoming intricate data challenges. They offer comprehensive solutions including data strategy design, data sourcing and collection (including synthetic data augmentation if needed), and robust human-in-the-loop processes. This approach ensures that AI models are trained with meticulously prepared data, tailored to specific project requirements and built for scalability and high performance.
Drawing on extensive experience in the data annotation field, Sigma AI assists clients in overcoming intricate data challenges. They offer comprehensive solutions including data strategy design, data sourcing and collection (including synthetic data augmentation if needed), and robust human-in-the-loop processes. This approach ensures that AI models are trained with meticulously prepared data, tailored to specific project requirements and built for scalability and high performance.
Features
- Data Labelling: Access to a global team of expert annotators, translators, and linguists for accurate data annotation.
- Data Strategy: Tailored design of efficient data preparation strategies for high-quality training data at scale.
- Data Collection: Sourcing, collecting, and curating necessary data, including synthetic data augmentation.
- Human-in-the-loop for LLM: Training, fine-tuning, and evaluation of LLMs using domain experts.
- Multi-language Support: Expertise in over 500 languages and dialects.
- High Accuracy: Delivers up to 99.99% accuracy for annotation tasks.
Use Cases
- Training Large Language Models (LLMs) with accurately labelled data.
- Developing Generative AI applications requiring high-quality datasets.
- Fine-tuning search algorithms using human evaluation of queries.
- Creating datasets for natural language processing tasks in specific dialects.
- Annotating images for product recognition in robotics and computer vision.
- Scaling transcription services across multiple languages.
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